HOW DO WE MANAGE DATA? Virginia T. McLemore New Mexico Bureau of Geology and Mineral Resources, New...
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Transcript of HOW DO WE MANAGE DATA? Virginia T. McLemore New Mexico Bureau of Geology and Mineral Resources, New...
HOW DO WE MANAGE HOW DO WE MANAGE DATA?DATA?
Virginia T. McLemore Virginia T. McLemore New Mexico Bureau of Geology New Mexico Bureau of Geology
and Mineral Resources, New and Mineral Resources, New Mexico Tech, Socorro, NMMexico Tech, Socorro, NM
PREVIEWPREVIEW
PurposePurpose Develop an exploration planDevelop an exploration plan Available dataAvailable data Sample theorySample theory Show example of databases for NMShow example of databases for NM Long-term database goalsLong-term database goals SummarySummary Unresolved issuesUnresolved issues
Purpose—continuedPurpose—continued
to make informed decisions aboutto make informed decisions about– explorationexploration– resource development and management resource development and management – water supplies water supplies – land useland use– environmental impacts environmental impacts – natural hazard assessmentnatural hazard assessment– waste disposalwaste disposal
EXPLORATION PLANEXPLORATION PLAN
What is the problem?What is the problem? What are the background conditions?What are the background conditions? What is the source of the What is the source of the
mineralization?mineralization? What are the pathways affected?What are the pathways affected? What are the desired final results?What are the desired final results? Is the site in compliance with Is the site in compliance with
environmental laws? environmental laws?
COMPONENTS OF A SAMPLING COMPONENTS OF A SAMPLING PLANPLAN
• Define questions and objectivesDefine questions and objectives• Develop site conceptual modelsDevelop site conceptual models
• Collect available pre-existing dataCollect available pre-existing data
• Costs and potential consequences of not Costs and potential consequences of not samplingsampling
• Identify types of data and information neededIdentify types of data and information needed• Define confidence level and quantity of data Define confidence level and quantity of data
required to answer questionsrequired to answer questions• Design the sampling planDesign the sampling plan
COMPONENTSCOMPONENTS—continued—continued
Develop protocolsDevelop protocols Conduct an orientation or pilot study Conduct an orientation or pilot study
before implementationbefore implementation Conduct sampling plan Conduct sampling plan Analyze and manage data Analyze and manage data
(interpretation) (interpretation) Make decisions (risk management) Make decisions (risk management) Educate and inform the parties involvedEducate and inform the parties involved
1. DEFINE QUESTIONS AND 1. DEFINE QUESTIONS AND
OBJECTIVESOBJECTIVES
Identify sources, transport, and effects of Identify sources, transport, and effects of mineralization. mineralization.
Validate predicative models.Validate predicative models. Validate Validate
exploration/mitigation/remediation/reclamation efforts.exploration/mitigation/remediation/reclamation efforts. Establish background or existing conditions.Establish background or existing conditions. Identify impacted areas vs. pristine areas.Identify impacted areas vs. pristine areas. Potential use of water in operations Potential use of water in operations
2. DEVELOP EXPLORATION 2. DEVELOP EXPLORATION
CONCEPTUAL MODELSCONCEPTUAL MODELS
Review existing dataReview existing data Climatic data Climatic data Physical data Physical data Geology (mineralogy)Geology (mineralogy) Hydrogeology (Surface-ground water interaction)Hydrogeology (Surface-ground water interaction) Mining history and impacts of mine workingsMining history and impacts of mine workings BiologyBiology Other data availableOther data available
We suggest that a watershed or district approach We suggest that a watershed or district approach be taken.be taken.
3. COSTS AND POTENTIAL 3. COSTS AND POTENTIAL
CONSEQUENCES OF NOT SAMPLINGCONSEQUENCES OF NOT SAMPLING
Avoid being data rich but information poor.Avoid being data rich but information poor. Public perceptions of risk.Public perceptions of risk. Perceptions of chemicals associated with Perceptions of chemicals associated with
the mining industry, such as cyanide.the mining industry, such as cyanide. Some long-term and widespread Some long-term and widespread
environmental problems should be environmental problems should be considered relatively high-risk even if the considered relatively high-risk even if the data on which the risk assessment is based data on which the risk assessment is based are somewhat incomplete and uncertain.are somewhat incomplete and uncertain.
4. IDENTIFY TYPES OF DATA AND 4. IDENTIFY TYPES OF DATA AND
INFORMATION NEEDEDINFORMATION NEEDED What sampling media (solid, liquid, What sampling media (solid, liquid,
biological/wetlands, air)?biological/wetlands, air)? What are sources, transport mechanisms, What are sources, transport mechanisms,
and receptors?and receptors? What type of sample is to be collected and What type of sample is to be collected and
is it representative?is it representative? What field measurements are required?What field measurements are required? What is the feasibility of sampling?What is the feasibility of sampling?
5. DEFINE CONFIDENCE LEVEL AND 5. DEFINE CONFIDENCE LEVEL AND QUANTITY OF DATA REQUIRED TO QUANTITY OF DATA REQUIRED TO
ANSWER QUESTIONSANSWER QUESTIONS
What is the confidence level needed?What is the confidence level needed? How much data are required?How much data are required?
6. DESIGN THE SAMPLING PLAN6. DESIGN THE SAMPLING PLAN
QA/QC QA/QC Data formatData format Safety issues (OSHA vs. MSHA vs. local, state Safety issues (OSHA vs. MSHA vs. local, state
vs. good neighbor/employer)vs. good neighbor/employer) Sample location, number of samples, and Sample location, number of samples, and
frequency of sampling, proper labeling of frequency of sampling, proper labeling of samples (site specific)samples (site specific)
What constituents or parameters are required What constituents or parameters are required for each media for each media
7. DEVELOP PROTOCOLS7. DEVELOP PROTOCOLS
Collection techniques Collection techniques Sample collectionSample collection Observational field data Observational field data Modify sampling plan and deviationsModify sampling plan and deviations Opportunistic samplingOpportunistic sampling ContaminationContamination Handling/transport Handling/transport Preservation and storage (from field to Preservation and storage (from field to
laboratory)laboratory)
7. DEVELOP PROTOCOLS—continued7. DEVELOP PROTOCOLS—continued
Sample pre-treatment in the laboratorySample pre-treatment in the laboratory Filtration Filtration Sample preparationSample preparation Sample separationSample separation Archival/storageArchival/storage Analytical procedures and techniquesAnalytical procedures and techniques
8. ORIENTATION OR PILOT STUDY8. ORIENTATION OR PILOT STUDY
Clear understanding of target typeClear understanding of target type Understanding of surficial environmentsUnderstanding of surficial environments Nature of dispersion from mineralized Nature of dispersion from mineralized
areasareas Sample types availableSample types available Sample collection proceduresSample collection procedures Sample size requirementsSample size requirements
8. ORIENTATION OR PILOT STUDY-8. ORIENTATION OR PILOT STUDY-continuedcontinued
Sample interval, depth, orientation, and Sample interval, depth, orientation, and densitydensity
Field observations requiredField observations required Sample preparation proceduresSample preparation procedures Sample fraction for analysesSample fraction for analyses Geochemical suite for analysesGeochemical suite for analyses Data format for interpretationData format for interpretation
10. ANALYZE AND MANAGE DATA10. ANALYZE AND MANAGE DATA
Reporting dataReporting data Presentation of dataPresentation of data InterpretationInterpretation Data interpretation approachesData interpretation approaches
– StatisticalStatistical
– SpatialSpatial
– GeochemicalGeochemical
– GeologicalGeological
10. ANALYZE AND MANAGE DATA—10. ANALYZE AND MANAGE DATA—continuedcontinued
Reporting and disseminationReporting and dissemination What becomes of data (storage)What becomes of data (storage) Common data formatsCommon data formats Use the dataUse the data Reliability and limitations of findings Reliability and limitations of findings Evaluate the data (statistics)Evaluate the data (statistics)
SAMPLING MEDIASAMPLING MEDIA
A variety of sampling media can be tested A variety of sampling media can be tested – solid solid – liquid liquid – airair– biologicalbiological– other mediaother media
AVAILABLE DATAAVAILABLE DATA Location (= GIS, point and polygon data)Location (= GIS, point and polygon data) Production, reserves, resource potentialProduction, reserves, resource potential GeologicGeologic Geochemical (rock, water, ect.)Geochemical (rock, water, ect.) Well dataWell data Historical and recent photographsHistorical and recent photographs Mining methods, mapsMining methods, maps Ownership Ownership Other dataOther data
OTHER DATAOTHER DATA Igneous rocks databaseIgneous rocks database Core and cuttings archiveCore and cuttings archive Geochronology databaseGeochronology database Mine mapsMine maps GIS-type dataGIS-type data
– geologygeology– geophysicsgeophysics– topographytopography– remote sensingremote sensing– well locations (cuttings, core, logs)well locations (cuttings, core, logs)
ENVIRONMENTAL DATAENVIRONMENTAL DATA Commodities produced and presentCommodities produced and present Potential hazardous materialsPotential hazardous materials Evidence of potential acid drainageEvidence of potential acid drainage HydrologyHydrology Receiving streamReceiving stream ReclamationReclamation Mitigation statusMitigation status Sensitive environmentsSensitive environments Chemical data (both solids and water)Chemical data (both solids and water)
Relational database in ACCESS Relational database in ACCESS that will ultimately be put on line that will ultimately be put on line
with GIS capabilitieswith GIS capabilities
ACCESS is commercial software and this ACCESS is commercial software and this design can be used by othersdesign can be used by others
metadata (supporting definitions of specific metadata (supporting definitions of specific fields) can be inserted into the databasefields) can be inserted into the database
ACCESS is flexible and data can be easily ACCESS is flexible and data can be easily added to the designadded to the design
GISGIS
Geologic Information SystemGeologic Information System– Arc MapArc Map– Arc CatalogArc Catalog
What is a sample?What is a sample?
Portion of a wholePortion of a whole Portion of a populationPortion of a population
Sample CollectionSample Collection
CompletenessCompleteness –– the comparison between the the comparison between the amount of valid, or usable, data you originally amount of valid, or usable, data you originally planned to collect, versus how much you planned to collect, versus how much you collected. collected.
Comparability –Comparability – the extent to which data can be the extent to which data can be compared between sample locations or periods compared between sample locations or periods of time within a project, or between projects. of time within a project, or between projects.
RepresentativenessRepresentativeness – the extent to which – the extent to which samples actually depict the true condition or samples actually depict the true condition or population that you are evaluatingpopulation that you are evaluating
““All analytical All analytical measurements are wrong: measurements are wrong: it’s just a question of how it’s just a question of how large the errors are, and large the errors are, and
whether they are whether they are acceptableacceptable” (Thompson, ” (Thompson,
1989).1989).
DEFINTIONSDEFINTIONS Precision –Precision – the degree of agreement among the degree of agreement among
repeated measurements of the same characteristic. repeated measurements of the same characteristic. Precision is monitored by multiple analyses of many Precision is monitored by multiple analyses of many sample duplicates and internal standards. sample duplicates and internal standards.
Accuracy –Accuracy – measures how close your results are to measures how close your results are to a a truetrue or expected value and can be determined by or expected value and can be determined by comparing your analysis of a standard or reference comparing your analysis of a standard or reference sample to its actual value. Analyzing certified sample to its actual value. Analyzing certified standards as unknown samples and comparing with standards as unknown samples and comparing with known certified values monitors accuracy. known certified values monitors accuracy.
QUALITY CONTROL/QUALITY QUALITY CONTROL/QUALITY ASSURRANCEASSURRANCE
QC is referred to a program designed to QC is referred to a program designed to detect and measure the error associated with detect and measure the error associated with a measurement process. QC is the program a measurement process. QC is the program that ensures that the data are acceptable. that ensures that the data are acceptable.
QA is the program designed to verify the QA is the program designed to verify the acceptability of the data using the data acceptability of the data using the data obtained from the QC program. QA provides obtained from the QC program. QA provides the assurance that the data meets certain the assurance that the data meets certain quality requirements with a specified level of quality requirements with a specified level of confidence. confidence.
QUALITY CONTROL/QUALITY QUALITY CONTROL/QUALITY ASSURRANCEASSURRANCE
What is the purpose of your project?What is the purpose of your project? What do you need the analyses for and how accurate should they be?What do you need the analyses for and how accurate should they be? Where are the results going to be released or published?Where are the results going to be released or published? What is the mineralogy?What is the mineralogy? What are appropriate certified standards (may need to develop lab What are appropriate certified standards (may need to develop lab
standards)?standards)? What are the detection limits (both upper and lower)?What are the detection limits (both upper and lower)?
– Analytical errors vary from element to element, for different ranges Analytical errors vary from element to element, for different ranges of concentration, and different methodsof concentration, and different methods
Duplicate or more analyses of standards and unknowns verses Duplicate or more analyses of standards and unknowns verses duplicate runs of same sampleduplicate runs of same sample
QUALITY CONTROL/QUALITY QUALITY CONTROL/QUALITY ASSURRANCEASSURRANCE
Analyze a separate set of standards rather than standards used Analyze a separate set of standards rather than standards used for calibrationfor calibration
Send samples and standards to other laboratoriesSend samples and standards to other laboratories Establish written lab proceduresEstablish written lab procedures Are blanks and field blanks used and analyzed?Are blanks and field blanks used and analyzed? What are the custody procedures (collection date, preservation What are the custody procedures (collection date, preservation
method, matrix, analytical procedures)?method, matrix, analytical procedures)? Does the chemical analyses make geological sense? Is it Does the chemical analyses make geological sense? Is it
consistent with the mineralogy and type of mineral deposit?consistent with the mineralogy and type of mineral deposit? Sometimes there is more paper work than making sure the data Sometimes there is more paper work than making sure the data
is accurateis accurate What do you do if there are problems with QA/QC?What do you do if there are problems with QA/QC?
TYPES OF ERRORSTYPES OF ERRORS
Systematic verses bias (constant, Systematic verses bias (constant, unintentional)unintentional)
Random errors (unpredicted but Random errors (unpredicted but nonsystematic errors, imprecise nonsystematic errors, imprecise practices)practices)
Gross or illegitimate errors (procedural Gross or illegitimate errors (procedural mistakes)mistakes)
Deliberate errorsDeliberate errors
MEASUREMENT ERRORSMEASUREMENT ERRORS
Wrong sampleWrong sample Wrong readingWrong reading Transposition or Transposition or
transcription errorstranscription errors Wrong calibrationWrong calibration Peak overlapPeak overlap Wrong methodWrong method ContaminationContamination
LossesLosses Inattention to detailsInattention to details Sampling problemsSampling problems Instrument instabilityInstrument instability Reagent controlReagent control Variability of blankVariability of blank Operator skillOperator skill Sample variabilitySample variability
Why do we need full chemical Why do we need full chemical analyses on some solid samples?analyses on some solid samples?
Identification of lithologyIdentification of lithology Identification and abundance of mineral speciesIdentification and abundance of mineral species Identification, rank, and intensity of alterationIdentification, rank, and intensity of alteration Prediction of composition of waters within rock Prediction of composition of waters within rock
pilespiles Chemical and mineralogical zonation of rock pilesChemical and mineralogical zonation of rock piles Be able to compare, contrast, and coordinate all Be able to compare, contrast, and coordinate all
phases of the project with each other and with phases of the project with each other and with existing work (common thread)existing work (common thread)
Standard Operating ProceduresStandard Operating Procedures
Develop SOPs prior to initiation of projectDevelop SOPs prior to initiation of project SOPS should be written and changed to SOPS should be written and changed to
reflect changing procedures—only if reflect changing procedures—only if procedures can be changedprocedures can be changed
SOPs are a written record of procedures in SOPs are a written record of procedures in useuse
Everyone follows SOPsEveryone follows SOPs
ExplorationExploration
Generally looking for anomaliesGenerally looking for anomalies Some value above backgroundSome value above background Looking for anomalies in pathfinder Looking for anomalies in pathfinder
elementselements Looking for alteration halosLooking for alteration halos
WHAT IS A PATHFINDER ELEMENT?WHAT IS A PATHFINDER ELEMENT?
How do you determine an How do you determine an anomaly?anomaly?
Knowledge of backgroundKnowledge of background– Regional surveyRegional survey– Published background values for Published background values for
various terrains or lithologiesvarious terrains or lithologies Histograms or cumulative Histograms or cumulative
frequency plots of datafrequency plots of data Pre-determined thresh holdPre-determined thresh hold
– Mined gradesMined grades
DATABASES FOR LUNA DATABASES FOR LUNA COUNTYCOUNTY
DistrictsDistricts Mines (and mills)Mines (and mills) GeochemistryGeochemistry PhotographsPhotographs
The term The term minemine is defined here is defined here as any mine, prospect, as any mine, prospect,
mineralized outcrop, altered mineralized outcrop, altered area, mill, smelter, or other area, mill, smelter, or other
mining-related facility, mining-related facility, including geothermal wells, including geothermal wells,
other mineral wells, excluding other mineral wells, excluding petroleum wells.petroleum wells.
Mine_id in some cases refers to Mine_id in some cases refers to one mine feature (adit, pit, shaft, one mine feature (adit, pit, shaft,
etc.) and in other cases to etc.) and in other cases to several mine features. If a mine several mine features. If a mine
occurs in 2 quadrangles or 2 occurs in 2 quadrangles or 2 counties, then it receives 2 counties, then it receives 2
separate Mine_id numbers. Large separate Mine_id numbers. Large mines receive one Mine_id and mines receive one Mine_id and
as many mine_feature id as many mine_feature id numbers as needed.numbers as needed.
District (miningdist.xls)District_idDistrict_or_coal_field*Aliases*County*Type_of_depositYear_of_discovery*Years_of_production*Commodities_produced*Commodities_present*Estimated_cumulative_ production_in original_dollars*Type_of_deposit*USGS_classification*References*Comments
Mines in district (dist_mine.xls)District_idDistrict_or_coal_fieldMine_idMine_name
Annual district production (dist_ann_prod.xls)District_idDistrictCountyYearCommodityQuantityUnits
Estimated productionDistrict_idDistrictCountyPeriod of productionCommodityQuantityUnitsReferencesCommentsActual production
District_idDistrictCountyPeriod of productionCommodityQuantityUnitsReferencesComments
Sample tableDistrict_idSample_id
Photograph tableDistrict_idPhotograph_id
BibliographyDistrict_idReference_idReference
DISTRICTSDISTRICTS
Mines (lunamines.mdb)Mine_idCountyDistrict_idDistrictMine_name*Aliases*Location*Township*Range*Section*SubsectionLatitudeLongitudeUtm_eastingUtm_northingUtm_zoneLocation_assurance*Commodities_produced*Commodities_present_ not_produced*Years_of_production*DevelopmentOperating status*Production*Mining_methods*Ownership
Samples tableMine_idSample_id
Photographs tableMine_idPhotograph_id
Patented minesMine_idMineral_survey_numberPatent_numberYear_patented
ProductionMine_idStartStopYearCommodityQuantityUnitsReference
BibliographyMine_idReference_idReference
Mine site specific data (ponds, mills, ect.)Mine_idFeature_idType_of_featureSample_numberDescriptionReferenceComments
Mineral_survey_number.Patent_numberYear_patentedMining_history*Age_host_rock*Host_formation*Rock_type*Structure*Mineralogy*Size*Alteration*Type_of_deposit*USGS_classification*USGS_quadrangle*Elevation*Sample_number*MRDS_number*Chemical_analyses*Photograph_number*CommentsRecommendations*References*Inspected_by*Date_inspected
MINESMINES
Sample tableSample_idMine_idDistrict_idCountyType of sampleSample descriptionLatitudeLongitudeLocation descriptionDepthDate collectedCollected byReference
Analyses tableSample_idLaboratory Data
BibliographySample_idReference_idReference
GEOCHEMISTRYGEOCHEMISTRY
PHOTOGRAPHSPHOTOGRAPHSPhotogaphsIDMine_idDistrict_idPrintNoColorOfPrintNegativeNoSlideNoColorOfSlideSlidesImageDivisionDatePhotographerCountyLocationKeywordsCaptionExtendedCaptionCourtesyOfCollectionCopyrightCopyrightCodeNoCreditCommentsScanImage
Actual photographsJpegs
BibliographyPhoto_IDReference_idReference
SUMMARYSUMMARY
Team effortTeam effort– database informationdatabase information– database design and linkagesdatabase design and linkages
StepsSteps– Design the database format ASAPDesign the database format ASAP– Data inputData input– Use subset of data to test the projectUse subset of data to test the project– Develop the final productDevelop the final product– Use itUse it